Facilitatory neural dynamics for predictive extrapolation

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Abstract

Neural conduction delay is a serious issue for organisms that need to act in real
time. Perceptual phenomena such as the flash-lag effect (FLE, where the position of
a moving object is perceived to be ahead of a brief flash when they are actually colocalized)
suggest that the nervous system may perform extrapolation to compensate
for delay. However, the precise neural mechanism for extrapolation has not been fully
investigated.
The main hypothesis of this dissertation is that facilitating synapses, with their
dynamic sensitivity to the rate of change in the input, can serve as a neural basis for
extrapolation. To test this hypothesis, computational and biologically inspired models
are proposed in this dissertation. (1) The facilitatory activation model (FAM) was
derived and tested in the motion FLE domain, showing that FAM with smoothing
can account for human data. (2) FAM was given a neurophysiological ground by
incorporating a spike-based model of facilitating synapses. The spike-based FAM was
tested in the luminance FLE domain, successfully explaining extrapolation in both
increasing and decreasing luminance conditions. Also, inhibitory backward masking
was suggested as a potential cellular mechanism accounting for the smoothing effect.
(3) The spike-based FAM was extended by combining it with spike-timing-dependent
plasticity (STDP), which allows facilitation to go across multiple neurons. Through STDP, facilitation can selectively propagate to a specific direction, which enables the
multi-neuron FAM to express behavior consistent with orientation FLE. (4) FAM
was applied to a modified 2D pole-balancing problem to test whether the biologically
inspired delay compensation model can be utilized in engineering domains. Experimental
results suggest that facilitating activity greatly enhances real time control
performance under various forms of input delay as well as under increasing delay and
input blank-out conditions.
The main contribution of this dissertation is that it shows an intimate link between
the organism-level problem of delay compensation, perceptual phenomenon of
FLE, computational function of extrapolation, and neurophysiological mechanisms
of facilitating synapses (and STDP). The results are expected to shed new light on
real-time and predictive processing in the brain, and help understand specific neural
processes such as facilitating synapses.